Satwik Kundu

W209 Westgate Building

University Park, PA

Hi! I am Satwik, currently a fourth-year Ph.D. candidate in Computer Science and Engineering at Penn State, specializing in quantum computing, machine learning and security. I am advised by Prof. Swaroop Ghosh. My research focuses on developing frameworks to enhance the security of quantum neural networks (QNNs) against adversarial threats, improving the efficiency of variational quantum algorithms (VQAs), and exploring applications of VQAs.

Before joining Penn State, I received my bachelor’s degree from Jadavpur University in 2021. Throughout my academic journey, I have worked on various projects, from creating facial expression recognition models to addressing microarchitectural security challenges in Docker containers.

News

Jun 2025	Awarded the prestigious `Harvey and Geraldine Brush Graduate Fellowship in Engineering`!
Jun 2025	Selected as a recipient of the `2024-25 Vice Provost and Dean of the Graduate School Student Persistence Scholarship`!
May 2025	`STIQ` received the Best Paper Award (1 out of 140+ submissions) at IEEE HOST 2025!
Apr 2025	Our paper, `Inverse-Transpilation`, has been accepted for presentation in the `Advances in Security of Quantum Computing` session at ACM GLSVLSI 2025!
Apr 2025	Our paper entitled `Adversarial Data Poisoning Attack on Quantum Machine Learning in the NISQ Era` has been accepted for oral presentation at ACM GLSVLSI 2025!
Nov 2024	Our paper, `STIQ: Safeguarding Training and Inferencing of Quantum Neural Networks from Untrusted Cloud`, has been accepted at IEEE HOST 2025!
Oct 2024	Gave a talk on `Security of Quantum Machine Learning` at QCCS 2024.
Sep 2024	Our paper entitled `SoK: Security Concerns in Quantum Machine Learning as a Service` has been accepted at ACM HASP 2024 (co-located with MICRO)!
Apr 2024	Passed my Ph.D. Comprehensive Exam!
Apr 2024	Our paper entitled `Evaluating Efficacy of Model Stealing Attacks and Defenses on Quantum Neural Networks` has been accepted at ACM GLSVLSI 2024!
Mar 2024	We received `$70,000` worth of credits from `IBM Quantum` for my research in improving efficiency of variational quantum algorithms (VQAs)!

Recent Publications

GLSVLSI

Adversarial Data Poisoning Attack on Quantum Machine Learning in the NISQ Era

Satwik Kundu, and Swaroop Ghosh

Proceedings of the 35th IEEE/ACM Great Lakes Symposium on VLSI (GLSVLSI), 2025

arXiv Bib

@article{kundu2024adversarial,
  title = {Adversarial Data Poisoning Attack on Quantum Machine Learning in the NISQ Era},
  author = {Kundu, Satwik and Ghosh, Swaroop},
  journal = {Proceedings of the 35th IEEE/ACM Great Lakes Symposium on VLSI (GLSVLSI)},
  year = {2025},
}

HOST

STIQ: Safeguarding Training and Inferencing of Quantum Neural Networks from Untrusted Cloud

Satwik Kundu, and Swaroop Ghosh

IEEE International Symposium on Hardware Oriented Security and Trust (HOST), 2025

🏆 Best Paper Award 🏆

arXiv Bib

@article{kundu2024stiq,
  title = {STIQ: Safeguarding Training and Inferencing of Quantum Neural Networks from Untrusted Cloud},
  author = {Kundu, Satwik and Ghosh, Swaroop},
  journal = {IEEE International Symposium on Hardware Oriented Security and Trust (HOST)},
  year = {2025},
  note = {🏆 Best Paper Award 🏆}
}

HASP

Security Concerns in Quantum Machine Learning as a Service

Satwik Kundu, and Swaroop Ghosh

13th ACM International Workshop on Hardware and Architectural Support for Security and Privacy (HASP) @ MICRO, 2024

URL arXiv Bib

@article{kundu2024security,
  title = {Security Concerns in Quantum Machine Learning as a Service},
  author = {Kundu, Satwik and Ghosh, Swaroop},
  journal = {13th ACM International Workshop on Hardware and Architectural Support for Security and Privacy (HASP) @ MICRO},
  year = {2024},
  url = {https://dl.acm.org/doi/10.1145/3696843.3696846},
}

GLSVLSI

Evaluating Efficacy of Model Stealing Attacks and Defenses on Quantum Neural Networks

Satwik Kundu, Debarshi Kundu, and Swaroop Ghosh

In Proceedings of the 34th IEEE/ACM Great Lakes Symposium on VLSI (GLSVLSI), 2024

URL arXiv Bib

@inproceedings{kundu2024evaluating,
  title = {Evaluating Efficacy of Model Stealing Attacks and Defenses on Quantum Neural Networks},
  author = {Kundu, Satwik and Kundu, Debarshi and Ghosh, Swaroop},
  booktitle = {Proceedings of the 34th IEEE/ACM Great Lakes Symposium on VLSI (GLSVLSI)},
  pages = {556--559},
  year = {2024},
  organization = {IEEE/ACM},
  url = {https://dl.acm.org/doi/abs/10.1145/3649476.3658806},
}

ASP-DAC

Knowledge Distillation in Quantum Neural Network Using Approximate Synthesis

Mahabubul Alam, Satwik Kundu, and Swaroop Ghosh

In Proceedings of the 28th IEEE/ACM Asia and South Pacific Design Automation Conference (ASP-DAC), 2023

URL Bib

@inproceedings{alam2023knowledge,
  title = {Knowledge Distillation in Quantum Neural Network Using Approximate Synthesis},
  author = {Alam, Mahabubul and Kundu, Satwik and Ghosh, Swaroop},
  booktitle = {Proceedings of the 28th IEEE/ACM Asia and South Pacific Design Automation Conference (ASP-DAC)},
  pages = {639--644},
  year = {2023},
  url = {https://dl.acm.org/doi/abs/10.1145/3566097.3567877},
}